Abstract
Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Poor experimental design and lack of scientific transparency may cause experimental biases that in turn affect data quality, robustness and reproducibility. Here, we pinpoint sources of experimental variability in conventional 2D cell-based cancer drug screens to determine the effect of confounders on cell viability for MCF7 and HCC38 breast cancer cell lines treated with platinum agents (cisplatin and carboplatin) and a proteasome inhibitor (bortezomib). Variance component analysis demonstrated that variations in cell viability were primarily associated with the choice of pharmaceutical drug and cell line, and less likely to be due to the type of growth medium or assay incubation time. Furthermore, careful consideration should be given to different methods of storing diluted pharmaceutical drugs and use of DMSO controls due to the potential risk of evaporation and the subsequent effect on dose-response curves. Optimization of experimental parameters not only improved data quality substantially but also resulted in reproducible results for bortezomib- and cisplatin-treated HCC38, MCF7, MCF-10A, and MDA-MB-436 cells. Taken together, these findings indicate that replicability (the same analyst re-performs the same experiment multiple times) and reproducibility (different analysts perform the same experiment using different experimental conditions) for cell-based drug screens can be improved by identifying potential confounders and subsequent optimization of experimental parameters for each cell line.
Highlights
Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery
Previous studies have shown that complete growth medium supplemented with fetal bovine serum (FBS) reduces the effect of proteasome inhibitor bortezomib on proteasome activity[27], thereby warranting the use of HuMEC medium for all drug treatments
Due to poor aqueous solubility, the pharmaceutical drugs were dissolved in DMSO according to the manufacturer’s instructions, further diluted with 1xPBS to the desired working concentration (1–10000 nM bortezomib and 2–1024 μM cisplatin/carboplatin), and stored at 4 °C for up to one week in Falcon TC-treated flat-bottom culture microplates (VWR)
Summary
Cancer drug development has been riddled with high attrition rates, in part, due to poor reproducibility of preclinical models for drug discovery. Several recent studies have attempted to address this issue by describing biological (e.g. differences in cell type, medium composition, seeding density) and technical factors (e.g. edge effect, as well as, differences in assay, drug concentration and treatment time, methods for cell counting) contributing to data replicability (the same analyst re-performs the same experiment multiple times) and data reproducibility (different analysts perform the same experiment using different experimental conditions, e.g. cell culture systems and reagents), few studies have proposed a strategy to identify and correct for sources of variability in drug response[6,7,16,18,19]. We show that suboptimal assay conditions can be improved, and together with suitable dose-response metrics can result in consistent data between laboratories
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
